Multi-task distribution and scheduling method for multi-core data stream processor

Through dynamic priority calculation and load prediction mechanism, the problem of inefficient scheduling in multi-core processors is solved, efficient resource utilization and rapid task response are achieved, and the overall performance of multi-core data stream processors is improved.

CN120448056AInactive Publication Date: 2025-08-08CHONGQING YUFENG ZHISHANG EDUCATION CONSULTING CO LTD
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Patent Information

Application Number
CN202510461702.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-14
Publication Date
2025-08-08
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The existing multi-core processor scheduling scheme cannot respond to changes in task characteristics and kernel status in real time, resulting in insufficiency of scheduling, serious waste of resources, and inability to effectively balance the load between each core.

Method used

Dynamic priority calculation and load prediction mechanism are adopted, and task allocation is monitored and adjusted in real time through task management module, kernel status monitoring module, priority calculation module and historical data recording module, task allocation is optimized, and resource allocation is optimized.

Benefits of technology

Real-time response to tasks and kernel state changes is achieved, scheduling efficiency is improved, core overload or idleness is avoided, overall system resource utilization and data processing throughput are improved, and performance needs of modern applications are met.

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Abstract

The invention discloses a multi-task allocation and scheduling method for a multi-core data stream processor. The method comprises the following steps: step 1, building a system architecture; 2, task collection and sparseness calculation; step 3, dynamic priority calculation; step 4, implementing a load prediction mechanism; step 5, task scheduling and distribution; and step 6, evaluating and optimizing the system. By introducing a dynamic priority adjustment mechanism, the system can respond to changes of task characteristics and kernel states in real time, the scheduling efficiency is remarkably improved, and the dynamic adaptability ensures that key tasks can preferentially obtain processing resources, so that the processing delay is reduced; through a load prediction mechanism, the load among the cores is effectively balanced, and the situation that some cores are overloaded and other cores are idle is avoided, so that the overall resource utilization rate of the system is improved, dynamic scheduling and load optimization are integrated, the system can keep efficient operation in a complex data stream processing scene, and the throughput and real-time response capability of data processing are improved.
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